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Mads Græsbøll Christensen

54 accepted papers

2025

A Modified Gain Normalized Step Size Adaptive Algorithm for Improved Online Secondary Path Modelling in Active Noise Control

Asutosh Kar, Gagandeep Singh, Pradeep K. Shill, Somanath Pradhan, Vasundhara, Mads Græsbøll Christensen
ICASSP 2025accepted

The noise cancellation performance of an active control system decreases when there are temporal variations in the primary and secondary paths. An active noise control (ANC) framework has been introduced in this work, which incorporates four adaptive filters and two decorrelation filters for online…

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2025

Advances in Microphone Array Processing and Multichannel Speech Enhancement

Gongping Huang, Jesper Rindom Jensen, Jingdong Chen, Jacob Benesty, Mads Græsbøll Christensen, Akihiko Sugiyama +2
ICASSP 2025accepted

This paper reviews pioneering works in microphone array processing and multichannel speech enhancement, highlighting historical achievements, technological evolution, commercialization aspects, and key challenges. It provides valuable insights into the progression and future direction of these areas…

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2025

Fractional-Order Hyperbolic Tangent Based Adaptive Algorithm for Feedback Control in Hearing Aids

Vanitha Devi R, Vasundhara, Asutosh Kar, Mads Græsbøll Christensen
ICASSP 2025accepted

A new method is suggested to improve the effectiveness of adaptive filters in dealing with unexpected disturbances at the error sensor. This method focuses specifically on the difficult scenario of α-stable noise in feedback cancellation for hearing aids. α-stable noise, which is distinguished by it…

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2025

Next-Generation ANC: Integrating Dynamic Fixed-Filter Strategies With Extended Kalman Filtering for Enhanced Noise Suppression

Fareedha, Vasundhara, Asutosh Kar, Mads Græsbøll Christensen
ICASSP 2025accepted

The hybrid selective fixed-filter active noise control with filtered reference normalized least mean square (SFANC-FxNLMS) method struggles in dynamic noise environments due to its reliance on static filters, which limits effectiveness when noise characteristics change rapidly. The generative fixed-…

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2025

Robust Exponential Hyperbolic Tangent Geman-McClure Based Identification of Nonlinear Systems

Neetu Chikyal, Vasundhara, Chayan Bhar, Asutosh Kar, Mads Græsbøll Christensen
ICASSP 2025accepted

This manuscript presents a new technique to improve the performance of adaptive filters in handling the non-Gaussian or impulsive noise environment. The conduct of the adaptive filter decays in the presence of impulsive noise or outliers. To improve the efficiency of the filtering technique, this wo…

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2025

Robust Fixed-Filter Sound Zone Control with Audio-Based Position Tracking

Sankha Subhra Bhattacharjee, Andreas Jonas Fuglsig, Flemming Christensen, Jesper Rindom Jensen, Mads Græsbøll Christensen
ICASSP 2025accepted

Performance of sound zone control (SZC) systems deployed in practical scenarios are highly sensitive to the location of the listener(s) and can degrade significantly when listener(s) are moving. This paper presents a robust SZC system that adapts to dynamic changes such as moving listeners and varyi…

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2025

Sound Zone Control Robust To Sound Speed Change

Sankha Subhra Bhattacharjee, Jesper Rindom Jensen, Mads Græsbøll Christensen
ICASSP 2025accepted

Sound zone control (SZC) implemented using static optimal filters is significantly affected by various perturbations in the acoustic environment, an important one being the fluctuation in the speed of sound, which is in turn influenced by changes in temperature and humidity (TH). This issue arises b…

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2024

Broadband Personal Sound Zone Control in the Presence of Nonlinearities

Sankha Subhra Bhattacharjee, Srikanth Burra, Jesper Rindom Jensen, Liming Shi, Guoli Ping, Jingkai Weng +1
ICASSP 2024accepted

Existing literature on sound zone control generally consider the signal model to be linear. However, this is seldom true in practice owing to nonlinear distortions arising from the loudspeakers, especially in consumer applications. In this paper, we propose a new signal model for personal sound zone…

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2024

Conjugate Gradient Based Adaptive Algorithm for Nonlinear AEC

Srikanth Burra, Asutosh Kar, Mads Græsbøll Christensen
ICASSP 2024accepted

Recently, to mitigate the loudspeaker-based distortion in the acoustic system, the functional link adaptive filter – based nonlinear acoustic echo cancellation (NAEC) algorithm has been proposed. However, the usage of sine and cosine functions in nonlinear modeling coupled with the steepest descent…

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2024

Improving Speech Attenuation in Headphones using Harmonic Model Decomposition and Multiple-Frequency ANC

Yurii Iotov, Sidsel Marie Nørholm, Peter John McCutcheon, Mads Græsbøll Christensen
ICASSP 2024accepted

In environments such as open offices, call centres, etc., speech is often the main disturbing source of ambient noise, reducing concentration and productivity. Active noise control (ANC) systems have difficulties in dealing with speech due to its non-stationary nature and constraints in the ANC syst…

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2023

Frequency Bin-Wise Single Channel Speech Presence Probability Estimation Using Multiple DNNS

Shuai Tao, Himavanth Reddy, Jesper Rindom Jensen, Mads Græsbøll Christensen
ICASSP 2023accepted

In this work, we propose a frequency bin-wise method to estimate the single-channel speech presence probability (SPP) with multiple deep neural networks (DNNs) in the short-time Fourier transform domain. Since all frequency bins are typically considered simultaneously as input features for conventio…

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2023

Sparse Bayesian Learning Based Three-Dimensional Imaging for Antenna Array Radar

Yuhan Li, Jesper Rindom Jensen, Maozhong Fu, Zhenmiao Deng, Mads Græsbøll Christensen
ICASSP 2023accepted

In recent years, the development of compressed sensing and sparse representation provide us with a broader perspective of three-dimensional (3-D) imaging. In this work, we propose a 3-D imaging method based on a sparse Bayesian learning(SBL) framework for antenna array radar. It solves the problem o…

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2023

Study And Design Of Robust Personal Sound Zones With Vast Using Low Rank Rirs

Sankha Subhra Bhattacharjee, Liming Shi, Guoli Ping, Xiaoxiang Shen, Mads Græsbøll Christensen
ICASSP 2023accepted

The performance of sound zone control algorithms are known to degrade significantly with changes in acoustic conditions including perturbations of control microphones' positions. In this work, we study the feasibility and effectiveness of using low rank approximations of RIRs to calculate sound zone…

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2022

A Bayesian Permutation Training Deep Representation Learning Method for Speech Enhancement with Variational Autoencoder

Yang Xiang, Jesper Lisby Højvang, Morten Højfeldt Rasmussen, Mads Græsbøll Christensen
ICASSP 2022accepted

Recently, variational autoencoder (VAE), a deep representation learning (DRL) model, has been used to perform speech enhancement (SE). However, to the best of our knowledge, current VAE-based SE methods only apply VAE to model speech signal, while noise is modeled using the traditional non-negative…

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2022

Computationally Efficient Fixed-Filter ANC for Speech Based on Long-Term Prediction for Headphone Applications

Yurii Iotov, Sidsel Marie Nørholm, Valiantsin Belyi, Mads Dyrholm, Mads Græsbøll Christensen
ICASSP 2022accepted

In some situations, such as open office spaces, speech can play the role of an unwanted and disturbing source of noise, and ANC headphones or earbuds might help to solve this problem. However, ANC in modern headphones is often based on a pre-calculated fixed-filter for practical reasons, like stabil…

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2022

Generation of Personal Sound Fields in Reverberant Environments Using Interframe Correlation

Liming Shi, Guoli Ping, Xiaoxiang Shen, Mads Græsbøll Christensen
ICASSP 2022accepted

Personal sound field control techniques aim to produce sound fields for different sound contents in different places of an acoustic space without interference. The limitations of the state-of-the-art methods for sound field control include high latency and computational complexity, especially in the…

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2022

Privacy-Preserving Distributed Expectation Maximization for Gaussian Mixture Model Using Subspace Perturbation

Qiongxiu Li, Jaron Skovsted Gundersen, Katrine Tjell, Rafal Wisniewski, Mads Græsbøll Christensen
ICASSP 2022accepted

Privacy has become a major concern in machine learning. In fact, the federated learning is motivated by the privacy concern as it does not allow to transmit the private data but only intermediate updates. However, federated learning does not always guarantee privacy-preservation as the intermediate…

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2022

Robust Pressure Matching with ATF Perturbation Constraints for Sound Field Control

Junqing Zhang, Liming Shi, Mads Græsbøll Christensen, Wen Zhang, Lijun Zhang, Jingdong Chen
ICASSP 2022accepted

Sound field control systems deployed in room acoustic environments require knowing the acoustic channel impulse responses between the loudspeakers and matching microphones, which are challenging to estimate accurately due to perturbations caused by such factors as temperature changes and sensors’ po…

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2022

Sparse Modeling of The Early Part of Noisy Room Impulse Responses with Sparse Bayesian Learning

Maozhong Fu, Jesper Rindom Jensen, Yuhan Li, Mads Græsbøll Christensen
ICASSP 2022accepted

A model of a room impulse response (RIR) is useful for a wide range of applications. Typically, the early part of a RIR is sparse, and its sparse structure allows for accurate and simple modeling of the RIR. The existing ℓ <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w…

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2021

A Novel NMF-HMM Speech Enhancement Algorithm Based on Poisson Mixture Model

Yang Xiang, Liming Shi, Jesper Lisby Højvang, Morten Højfeldt Rasmussen, Mads Græsbøll Christensen
ICASSP 2021accepted

In this paper, we propose a novel non-negative matrix factorization (NMF) and hidden Markov model (NMF-HMM) based speech enhancement algorithm, which employs a Poisson mixture model (PMM). Compared to the previously proposed NMF-HMM method, the new algorithm, termed PMM-NMF-HMM, uses the Poisson mix…

Cited by 5Source ↗Scholar ↗
2020

A Fast Reduced-Rank Sound Zone Control Algorithm Using The Conjugate Gradient Method

Liming Shi, Taewoong Lee, Lijun Zhang, Jesper Kjær Nielsen, Mads Græsbøll Christensen
ICASSP 2020accepted

Sound zone control enables different users to enjoy different audio contents in the same acoustic environment. Generalized eigenvalue decomposition (GEVD)-based methods allow us to control the tradeoff between the acoustic contrast (AC) and signal distortion (SD). However, such methods have a high c…

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2020

Autoregressive Parameter Estimation with Dnn-Based Pre-Processing

Zihao Cui, Changchun Bao, Jesper Kjær Nielsen, Mads Græsbøll Christensen
ICASSP 2020accepted

In this paper, a method for estimating the autoregressive parameters from a signal segment is proposed. The method is based on a deep neural network (DNN) in combination with the classical Levinson-Durbin recursion (LDR). The DNN acts as a pre-processor for the LDR and can be trained on different me…

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2020

Convex Optimisation-Based Privacy-Preserving Distributed Average Consensus in Wireless Sensor Networks

Qiongxiu Li, Richard Heusdens, Mads Græsbøll Christensen
ICASSP 2020accepted

In many applications of wireless sensor networks, it is important that the privacy of the nodes of the network be protected. Therefore, privacy-preserving algorithms have received quite some attention recently. In this paper, we propose a novel convex optimization-based solution to the problem of pr…

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2020

Robust Fundamental Frequency Estimation in Coloured Noise

Alfredo Esquivel Jaramillo, Andreas Jakobsson, Jesper Kjær Nielsen, Mads Græsbøll Christensen
ICASSP 2020accepted

Most parametric fundamental frequency estimators make the implicit assumption that any corrupting noise is additive, white Gaus-sian. Under this assumption, the maximum likelihood (ML) and the least squares estimators are the same, and statistically efficient. However, in the coloured noise case, th…

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2019

A Study on How Pre-whitening Influences Fundamental Frequency Estimation

Alfredo Esquivel Jaramillo, Jesper Kjær Nielsen, Mads Græsbøll Christensen
ICASSP 2019accepted

This paper deals with the influence of pre-whitening for the task of fundamental frequency estimation in noisy conditions. Parametric fundamental frequency estimators commonly assume that the noise is white and Gaussian and, therefore, they are only statistically efficient under those conditions. Th…

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2019

Estimation of Guitar String, Fret and Plucking Position Using Parametric Pitch Estimation

Jacob Møller Hjerrild, Mads Græsbøll Christensen
ICASSP 2019accepted

In this paper a fast yet effective method is proposed for analyzing guitar performances. Specifically, the activated string and fret as well as the location of the plucking event along the guitar string are extracted from guitar signal recordings. The method is based on a parametric pitch estimator…

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2019

Hearing Aid-controlled Beamformer for Binaural Speech Enhancement Using a Model-based Approach

Mathew Shaji Kavalekalam, Jesper Kjær Nielsen, Mads Græsbøll Christensen, Jesper Bünsow Boldt
ICASSP 2019accepted

The understanding of speech from a particular speaker in the presence of other interfering speakers can be severely degraded for a hearing impaired person. Beamforming techniques have been proven to be effective to improve the speech understanding in such scenarios. However, the number of microphone…

Cited by 5Source ↗Scholar ↗
2019

Quality Control of Voice Recordings in Remote Parkinson's Disease Monitoring Using the Infinite Hidden Markov Model

Amir Hossein Poorjam, Yordan P. Raykov, Reham Badawy, Jesper Rindom Jensen, Mads Græsbøll Christensen, Max A. Little
ICASSP 2019accepted

The performance of voice-based systems for remote monitoring of Parkinson's disease is highly dependent on the degree of adherence of the recordings to the test protocols, which probe for specific symptoms. Identifying segments of the signal that adhere to the protocol assumptions is typically perfo…

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2019

Towards Perceptually Optimized Sound Zones: A Proof-of-concept Study

Taewoong Lee, Jesper Kjær Nielsen, Mads Græsbøll Christensen
ICASSP 2019accepted

The creation of sound zones has been an active research topic for approximately two decades. Many sound zone control methods have been proposed, and the best approaches result in a target to interferer ratio (TIR) of about 15 dB in a practical set-up. Unfortunately, this is far from a TIR of about 2…

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2018

A Parametric Approach for Classification of Distortions in Pathological Voices

Amir Hossein Poorjam, Max A. Little, Jesper Rindom Jensen, Mads Græsbøll Christensen
ICASSP 2018accepted

In biomedical acoustics, distortion in voice signals, commonly present during acquisition and transmission, adversely affects acoustic features extracted from pathological voice. Information on the type of distortion can help in compensating for its effects. This paper proposes a new approach to det…

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2018

A Study of Noise PSD Estimators for Single Channel Speech Enhancement

Mathew Shaji Kavalekalam, Jesper Kjær Nielsen, Mads Græsbøll Christensen, Jesper Bünsow Boldt
ICASSP 2018accepted

The estimation of the noise power spectral density (PSD) forms a critical component of several existing single channel speech enhancement systems. In this paper, we evaluate one new and some of the existing and commonly used noise PSD estimation algorithms in terms of the spectral estimation accurac…

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2018

A Supervised Approach to Global Signal-to-Noise Ratio Estimation for Whispered and Pathological Voices

Amir Hossein Poorjam, Max A. Little, Jesper Rindom Jensen, Mads Græsbøll Christensen
ICASSP 2018accepted

The presence of background noise in signals adversely affects the performance of many speech-based algorithms. Accurate estimation of signal-to-noise-ratio (SNR), as a measure of noise level in a signal, can help in compensating for noise effects. Most existing SNR estimation methods have been devel…

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2018

A Unified Approach to Generating Sound Zones Using Variable Span Linear Filters

Taewoong Lee, Jesper Kjær Nielsen, Jesper Rindom Jensen, Mads Græsbøll Christensen
ICASSP 2018accepted

Sound zones are typically created using Acoustic Contrast Control (ACC), Pressure Matching (PM), or variations of the two. ACC maximizes the acoustic potential energy contrast between a listening zone and a quiet zone. Although the contrast is maximized, the phase is not controlled. To control both…

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2018

Estimation of Source Panning Parameters and Segmentation of Stereophonic Mixtures

Jacob Moller Hjerrild, Mads Græsbøll Christensen
ICASSP 2018accepted

In this paper, we propose a method for finding the number of sources and their parameters from stereophonic mixtures. The method is based on clustering of narrowband interaural level and time differences for an unknown number of sources and uses an optimal segmentation on which the clustering is bas…

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2018

Model-Based Noise PSD Estimation from Speech in Non-Stationary Noise

Jesper Kjær Nielsen, Mathew Shaji Kavalekalam, Mads Græsbøll Christensen, Jesper Bünsow Boldt
ICASSP 2018accepted

Most speech enhancement algorithms need an estimate of the noise power spectral density (PSD) to work. In this paper, we introduce a model-based framework for doing noise PSD estimation. The proposed framework allows us to include prior spectral information about the speech and noise sources, can be…

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2018

Multipitch Estimation Using Block Sparse Bayesian Learning and Intra-Block Clustering

Liming Shi, Jesper Rindom Jensen, Jesper Kjær Nielsen, Mads Græsbøll Christensen
ICASSP 2018accepted

Pitch estimation is an important task in speech and audio analysis. In this paper, we present a multi-pitch estimation algorithm based on block sparse Bayesian learning and intra-block clustering for speech analysis. A statistical hierarchical model is formulated based on a pitch dictionary with a f…

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2017

Distributed max-SINR speech enhancement with ad hoc microphone arrays

Vincent Mohammad Tavakoli, Jesper Rindom Jensen, Richard Heusdens, Jacob Benesty, Mads Græsbøll Christensen
ICASSP 2017accepted

In recent years, signal processing with ad hoc microphone arrays has attracted a lot of attention. Speech enhancement in noisy, interfered, and reverberant environments is one of the problems targeted by ad hoc microphone arrays. Most of the proposed solutions require knowledge of fingerprints, such…

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2017

Estimation of multiple pitches in stereophonic mixtures using a codebook-based approach

Martin Weiss Hansen, Jesper Rindom Jensen, Mads Græsbøll Christensen
ICASSP 2017accepted

In this paper, a method for multi-pitch estimation of stereophonic mixtures of multiple harmonic signals is presented. The method is based on a signal model which takes the amplitude and delay panning parameters of the sources in a stereophonic mixture into account. Furthermore, the method is based…

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2017

Fast harmonic chirp summation

Jesper Kjær Nielsen, Tobias Lindstrøm Jensen, Jesper Rindom Jensen, Mads Græsbøll Christensen, Søren Holdt Jensen
ICASSP 2017accepted

The harmonic chirp signal model has only very recently been introduced for modelling approximately periodic signals with a time-varying fundamental frequency. A number of estimators for the parameters of this model have already been proposed, but they are either inaccurate, non-robust to noise, or v…

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2017

Harmonic minimum mean squared error filters for multichannel speech enhancement

Jesper Rindom Jensen, Mads Græsbøll Christensen, Andreas Jakobsson
ICASSP 2017accepted

Many state-of-the-art multichannel speech enhancement methods rely on second-order statistics of the desired speech signal, the noise signal, or both. Estimation of those are difficult in practice, resulting in a practical performance that is typically much lower than their potential theoretical per…

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2017

Least 1-norm pole-zero modeling with sparse deconvolution for speech analysis

Liming Shi, Jesper Rindom Jensen, Mads Græsbøll Christensen
ICASSP 2017accepted

In this paper, we present a speech analysis method based on sparse pole-zero modeling of speech. Instead of using the all-pole model to approximate the speech production filter, a pole-zero model is used for the combined effect of the vocal tract; radiation at the lips and the glottal pulse shape. M…

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2017

Model based binaural enhancement of voiced and unvoiced speech

Mathew Shaji Kavalekalam, Mads Græsbøll Christensen, Jesper Bünsow Boldt
ICASSP 2017accepted

This paper deals with the enhancement of speech in presence of non-stationary babble noise. A binaural speech enhancement framework is proposed which takes into account both the voiced and unvoiced speech production model. The usage of this model in enhancement requires the Short term predictor (STP…

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2017

Pitch-based non-intrusive objective intelligibility prediction

Charlotte Sorensen, Angeliki Xenaki, Jesper Bünsow Boldt, Mads Græsbøll Christensen
ICASSP 2017accepted

Automatic adjustment of the hearing aid according to the intelligibility for the user in the environment could be beneficial. While most intelligibility metrics require a clean speech reference, i.e. intrusive methods, this is rarely available in real-life. This paper proposes a non-intrusive intell…

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2016

A partitioned approach to signal separation with microphone ad hoc arrays

Vincent Mohammad Tavakoli, Jesper Rindom Jensen, Jacob Benesty, Mads Græsbøll Christensen
ICASSP 2016accepted

In this paper, a blind algorithm is proposed for speech enhancement in multi-speaker scenarios, in which interference rejection is the main objective. Here, the ad hoc array is broken into microphone duples which are used to partition the array into local sub-arrays. The core algorithm takes advanta…

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2016

DOA estimation of audio sources in reverberant environments

Jesper Rindom Jensen, Jesper Kjær Nielsen, Richard Heusdens, Mads Græsbøll Christensen
ICASSP 2016accepted

Reverberation is well-known to have a detrimental impact on many localization methods for audio sources. We address this problem by imposing a model for the early reflections as well as a model for the audio source itself. Using these models, we propose two iterative localization methods that estima…

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2016

Experimental study of generalized subspace filters for the cocktail party situation

Knud B. Christensen, Mads Græsbøll Christensen, Jesper Bünsow Boldt, Fredrik Gran
ICASSP 2016accepted

This paper investigates the potential performance of generalized subspace filters for speech enhancement in cocktail party situations with very poor signal/noise ratio, e.g. down to -15 dB. Performance metrics output signal/noise ratio, signal/distortion ratio, speech quality rating and speech intel…

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2016

Fast and statistically efficient fundamental frequency estimation

Jesper Kjær Nielsen, Tobias Lindstrøm Jensen, Jesper Rindom Jensen, Mads Græsbøll Christensen, Søren Holdt Jensen
ICASSP 2016accepted

Fundamental frequency estimation is a very important task in many applications involving periodic signals. For computational reasons, fast autocorrelation-based estimation methods are often used despite parametric estimation methods having superior estimation accuracy. However, these parametric meth…

Cited by 10Source ↗Scholar ↗
2016

Kalman filter for speech enhancement in cocktail party scenarios using a codebook-based approach

Mathew Shaji Kavalekalam, Mads Græsbøll Christensen, Fredrik Gran, Jesper Bünsow Boldt
ICASSP 2016accepted

Enhancement of speech in non-stationary background noise is a challenging task, and conventional single channel speech enhancement algorithms have not been able to improve the speech intelligibility in such scenarios. The work proposed in this paper investigates a single channel Kalman filter based…

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2015

On frequency domain models for TDOA estimation

Jesper Rindom Jensen, Jesper Kjær Nielsen, Mads Græsbøll Christensen, Søren Holdt Jensen
ICASSP 2015accepted

Time-difference-of-arrival (TDOA) estimation is an important problem in many microphone signal processing applications. Traditionally, this problem is solved by using a cross-correlation method, but in this paper we show that the cross-correlation method is actually a restricted special case of a mu…

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2015

Pitch and TDOA-based localization of acoustic sources with distributed arrays

Martin Weiss Hansen, Jesper Rindom Jensen, Mads Græsbøll Christensen
ICASSP 2015accepted

In this paper, a method for acoustic source localization using distributed microphone arrays based on time-differences of arrival (TDOAs) is presented. The TDOAs are used to estimate the location of an acoustic source using a recently proposed method, based on a 4D parameter space defined by the 3D…

Cited by 1Source ↗Scholar ↗
2015

Pitch estimation and tracking with harmonic emphasis on the acoustic spectrum

Sam Karimian-Azari, Nasser Mohammadiha, Jesper Rindom Jensen, Mads Græsbøll Christensen
ICASSP 2015accepted

In this paper, we use unconstrained frequency estimates (UFEs) from a noisy harmonic signal and propose two methods to estimate and track the pitch over time. We assume that the UFEs are multivariate-normally-distributed random variables, and derive a maximum likelihood (ML) pitch estimator by maxim…

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2015

Pseudo-coherence-based MVDR beamformer for speech enhancement with ad hoc microphone arrays

Vincent Mohammad Tavakoli, Jesper Rindom Jensen, Mads Græsbøll Christensen, Jacob Benesty
ICASSP 2015accepted

Speech enhancement with distributed arrays has been met with various methods. On the one hand, data independent methods require information about the position of sensors, so they are not suitable for dynamic geometries. On the other hand, Wiener-based methods cannot assure a distortionless output. T…

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